class_docstr: Sammon mapping function
docstr: Simple test case where the points are in a 2d circle.
docstr_tok: ["Simple","test","case","where","the","points","are","in","a","2d","circle","."]
code: def from_2d_circle(cls, num_points: int = 12) -> "SammonMapping":
      """Simple test case where the points are in a 2d circle."""
      idata = np.exp(np.linspace(0, 2 * np.pi, num_points) * 1j)
      data = np.zeros((num_points, 2))
      data[:, 0] = np.real(idata)
      data[:, 1] = np.imag(idata)
      instance = cls(scipy.spatial.distance_matrix(data, data))
      instance.add_descriptors(name="circle", num_points=num_points)
      return instance
  
imports: import numpy
  import pandas
  import scipy.spatial
  from nevergrad.parametrization import parameter
  import nevergrad.common.typing
  from ..base import ExperimentFunction
  from .None import datasets
label_desc: Use image node_id 3 for calling the SammonMapping obj's underlying member method code with example usage: obj.from_2d_circle(cls, num_points) and returns: instance